Selective space reclamation of data storage memory employing heat and relocation metrics

ABSTRACT

Space of a data storage memory of a data storage memory system is reclaimed by determining heat metrics of data stored in the data storage memory; determining relocation metrics related to relocation of the data within the data storage memory; determining utility metrics of the data relating the heat metrics to the relocation metrics for the data; and making the data whose utility metric fails a utility metric threshold, available for space reclamation.

CROSS-REFERENCE TO RELATED APPLICATIONS

This Application is a Continuation of U.S. patent application Ser. No.13/285,890, filed on Oct. 31, 2011.

FIELD OF THE INVENTION

This invention relates to computer-implemented data storage memories,and more particularly to memory space reclamation.

BACKGROUND OF THE INVENTION

Computer-implemented data storage systems typically comprise varioustypes of data storage in which data is stored on behalf of host computersystems. Storage controls control access to data storage media andmemories in response to read and write requests. The storage controlsmay direct the data in accordance with data storage memories and devicessuch as cache, non-volatile storage, RAID (redundant array ofindependent disks), JBOD (just a bunch of disks), etc. arranged intovarious redundancy, access speed and security levels.

As an example, an International Business Machines Corp. (IBM®) ESS(Enterprise Storage Server) such as a DS8000™ has redundant clusters ofcomputer entities, cache memories, non-volatile storage, etc., called“central electronics complexes” or “CECs”.

Within a data storage system, fast memories may be employed as cacheused to store data or instructions that were accessed recently, areaccessed frequently, or are likely to be accessed in the near future.Data stored in cache memories can be accessed quickly instead of beingfetched or recomputed, saving both time and resources.

Cache memories can be provided in multiple levels. For example, a cachedata storage system may comprise both a “first” or “primary” cachememory and a “secondary” cache memory. Typically, the first cache memoryhas faster access and is more costly per unit of data than a secondarycache memory, and the secondary cache memory has greater storagecapacity than the first cache memory. For example, a first cache memorycomprises DRAM (“dynamic random access memory”), while the secondarycache comprises flash memory solid-state drives (SSDs) such as“Flash_Cache” (TM International Business Corp.). When accessing data, acomputing system or device may first look for data in the first cachememory and, if the data is not present there, look for the data in thesecondary cache memory. When data is not available in either memory, ittypically is accessed from the major data storage which comprises sloweraccess speed data storage such as RAID, JBOD, etc. When data is read, ittypically remains in the major data storage and is copied to the firstcache memory and/or the secondary cache memory. If read data in thefirst cache memory is not accessed promptly or frequently, it may bedemoted to the secondary cache memory or evicted. If read data in thesecondary cache memory is not accessed promptly or frequently, it may beevicted. When writing data, a computing system or device may write datato the first cache memory. If write data in the first cache is notaccessed promptly or frequently, this data may be demoted to thesecondary cache memory. If data is not accessed promptly or frequentlyfrom the secondary cache memory, it may be demoted to the slower accessspeed data storage such as RAID, JBOD, etc. Alternatively, write datamay be written to the major data storage as soon as possible after beingreceived by the data storage system.

Typically, a LRU (least recently used) algorithm is employed to demotedata to the next lower level or to evict data from the first cachememory or the secondary cache memory.

In some memories, such as a secondary cache memory, the data is storedin log-structured fashion (written sequentially, requiring a log todetermine where data is stored on a logical basis) as pages in largeextents of data. The data pages are reviewed under a LRU algorithm, andthe least recently used pages are invalidated. To reclaim space, thesystem will select the log-structured extents (LSEs) that have the mostinvalidated pages and compact the valid pages, relocating them in newLSEs, leaving one or more LSEs free. The relocations incur a largenumber of I/O (input/output) relocation operations, as many LSEs need tobe read and one or more LSEs written at each iteration of thereclamation process.

SUMMARY OF THE INVENTION

Methods, computer-implemented data storage memory systems, and computerprogram products are provided for reclaiming space of a data storagememory of a data storage memory system. “Memory” in this context is anytype of memory having to invalidate, evict or demote data to make spaceavailable for new incoming data, an example of which is a cache memory.

In one embodiment of a computer-implemented data storage memory system,the following is performed:

determining heat metrics of data stored in the data storage memory;

determining relocation metrics related to relocation of the data withinthe data storage memory;

determining utility metrics of the data relating the heat metrics to therelocation metrics for the data; and

making the data whose utility metric fails a utility metric threshold,available for space reclamation.

Thus, data that otherwise may be saved, but that fails the utilitymetric threshold, is instead invalidated, and does not have to berelocated in the data storage memory.

In a further embodiment, data whose utility metric meets or exceeds theutility metric threshold is exempted from space reclamation eligibility.

In a further embodiment, data recently added to the data storage memoryis exempted from space reclamation eligibility.

In a still further embodiment, data designated as ineligible by spacemanagement policy is exempted from space reclamation eligibility.

In another embodiment, the utility metric threshold is determined froman average of utility metrics for data of the data storage memory.

In a further embodiment, the average of utility metrics for data of thedata storage memory is determined over a period of time or apredetermined number of requests processed.

In still another embodiment, the utility metric threshold is dynamicallydetermined from an average of utility metrics for data of the datastorage identified in an LRU list for the data storage memory.

In yet another embodiment, the data stored in the data storage memory isin the form of pages, and the utility metric threshold for a tentativespace reclamation victim page of the data, is dynamically determinedfrom an average of utility metrics for pages of the data having similarheat metrics to the tentative space reclamation victim.

In another embodiment, the data stored in the data storage memory is inthe form of pages in log structured extents; and the method additionallycomprises:

invalidating pages of the data eligible for reclamation;

selecting at least one log structured extent having the greatest numberof invalidated pages, for relocating valid pages therein into anotherlog structured extent, to reclaim the selected log structured extent.

In a further embodiment, the heat metric is based upon the number ofhits to data whose heat metric is being determined; and the relocationmetric is based upon the number of times the data whose relocationmetric is being determined is relocated to another log structuredextent.

For a fuller understanding of the present invention, reference should bemade to the following detailed description taken in conjunction with theaccompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an exemplary network andcomputer-implemented storage server system in which the presentinvention may be implemented;

FIG. 2 is a diagrammatic illustration of a computer-implemented datastorage memory system of FIG. 1;

FIG. 3 is a diagrammatic illustration of an extent of data stored by thedata storage memory system of FIG. 2; and

FIG. 4 is a flow chart depicting an exemplary method of operating thesystem of FIGS. 1 and 2.

DETAILED DESCRIPTION OF THE INVENTION

This invention is described in preferred embodiments in the followingdescription with reference to the Figures, in which like numbersrepresent the same or similar elements. While this invention isdescribed in terms of the best mode for achieving this invention'sobjectives, it will be appreciated by those skilled in the art thatvariations may be accomplished in view of these teachings withoutdeviating from the spirit or scope of the invention.

Referring to FIG. 1, an example of computer-based network architecture100 is illustrated with a computer-implemented data storage system 110which may implement a computer-implemented cache data storage system andmethods discussed herein. The architecture 100 is presented only by wayof example and is not intended to be limiting. The computer-implementedcache data storage system and methods disclosed herein may be applicableto a wide variety of different computers, servers, data storage systems,and network architectures.

The exemplary network architecture 100 may comprise one or more hostcomputer systems 102 coupled to a network, such as a storage areanetwork (SAN) 108. The network 108 may comprise any suitable private orpublic interconnection using any suitable protocol. The storage system110 comprises a storage control 200 configured to transfer data to andfrom and to control the operation of switches 202 and data storage 203and 204. The data storage may comprise, for example, arrays ofsolid-state drives and hard disk drives accessible via switches 202.Alternatively or additionally, the data storage 203 and 204 may compriseindividual devices or may comprise data storage libraries with manydevices. All or any of the host systems 102 may direct and utilize thestorage system 110 and utilize the storage control 200 and data cachingsystem herein.

The caching system may be implemented within a storage control 200 andmay also be applicable to other storage systems. As shown, the storagecontrol 200 comprises one or more servers 206. The control 200 may alsocomprise host adapters 208 and device adapters 210 to provide theinterfaces to connect the control 200 to host systems 102 and datastorage 203 and 204, respectively. Multiple servers 206 a, 206 b mayprovide redundancy to ensure that data is always available to connectedhosts 102. Thus, should one server 206 a fail, the other server 206 bmay remain functional to ensure that data transfer is able to continuebetween the host systems 102 and the data storage 203 and 204. Thisprocess may be referred to as “failover”.

One example of a storage system 110 having an architecture similar tothat illustrated in FIG. 1 is the DS8000™ Enterprise Storage Server ofInternational Business Machines Corp. (IBM®). The DS8000™ is a highperformance, high capacity storage control providing data storage thatis designed to support continuous operations and implementvirtualization of data storage, and is presented herein only by way ofembodiment examples and is not intended to be limiting. Thus, the memorydata storage system discussed herein is not limited to the DS8000™, butmay be implemented in any comparable storage control 200 having memorydata invalidation, regardless of the manufacturer, product name, orcomponents or component names associated with the system 110.

In the example of FIG. 1, each server 206 may comprise one or morecomputer processors 212 and memory 214. The computer processors 212 maycomprise internal processing and storage capabilities to store softwaremodules that run on the processors and, inter alia, are used to accessdata in the data storage 203 and 204.

In one embodiment, the memory 214 may comprise a cache 218. Whenever ahost 102 accesses data from the storage system 110, for example in aread operation, the server 206 that performs the operation, for examplereading data from storage 203 and 204, may save the data in its cache218 in the event the data may be required again. If the data is accessedagain by a host 102, the server 206 may fetch the data from the cache218 instead of fetching it from storage 203 and 204, saving both timeand resources. Similarly, when a host system 102 performs a write, theserver 206 may store, or host system 102 may direct that the data bestored, in cache 218 to be destaged to the storage 203 and 204 at alater time. When a write is stored in cache 218, the write may also bestored in non-volatile storage (NVS) 220 of the opposite server 206 sothat the write can be recovered by the opposite server 206 in the eventthe first server 206 fails.

Referring to FIGS. 1 and 2, a storage system 110 may comprise both datastorage 204, such as hard disk drives, and data storage 203, such assolid state drives (SSDs) based on flash memory. The input/output (I/O)performance of SSD drives or other types of solid state memory istypically far faster than the I/O performance of hard disk drives.Because of the higher I/O performance, the SSDs 203 may, in certainembodiments, be used to provide a large secondary cache 300 between thecache 218, serving as a first cache, and the hard disk drives 204. Theuse of a large secondary cache 300 may significantly improve the I/Operformance of the storage system 110.

Using the secondary cache 300 if a read request is received by a server206, the server may initially look for data in the first cache 218 and,if the data is not present, look for the data in the secondary cache 300residing in the SSDs 203. If the data is not available in either cache,the server 206 may retrieve the data from the hard disk drives 204.Similarly, when writing or modifying data, a server 206 may initiallywrite the data or modified data to the first cache 218. The data mayeventually be destaged to the secondary cache 300 to make room in thefirst cache 218. This data may ultimately be destaged to the disk drives204 to make space available in the secondary cache 300.

As an example, the secondary cache 300 may be sized to provide about oneto twenty percent of the total data storage capacity of the storagesystem 110. Thus, for a storage system 110 that comprises about 40terabytes of data storage (from both hard disk drives 204 and SSDs 203),about 2 terabytes of this storage space may be used as a secondary cache300. The first cache 218 is typically a small percentage of the size ofthe secondary cache 300. As an exemplary embodiment, the storage spacefor both the first cache 218 and the secondary cache 300 may be arrangedin pages to provide ease of handling.

Referring to FIGS. 2, 3 and 4, in one embodiment, space must bereclaimed in the first cache 218 and also in the secondary cache 300 toaccommodate new data. Similarly, all memories, once full, must provide ameans for reclaiming space in order to accommodate new data. Asdiscussed above, in some memories, such as a secondary cache memory, thedata is stored in log-structured fashion in large extents 280 of data aspages 285. The control 200 of FIG. 1 tracks the data pages, for example,with metadata, at the data handling information 320. A property of thelog-structured extents (LSE) is that all writes are sequential writes,an advantage when the memory 300 comprises SSDs. Another advantage isthat multiple pages may be written to the memory using a single I/O(input/output) operation. Still another advantage is that the internalbookkeeping for an LSE can be accomplished using a small header 290 atthe beginning of the LSE 280. Alternatively, the small header 290 mayalso be placed elsewhere in the extent, such as at the end of theextent. A disadvantage is discussed above and is that the valid pagesmay be relocated, and may be relocated many times, as the LSEs arecombined and rearranged to reclaim space in the form of empty LSEs.

In one embodiment, the data pages are reviewed under a LRU algorithm toprovide an LRU list 330, which can be considered as nominating pages tobe invalidated. As above, if a page is retained and not invalidated, butis in an LSE that comprises a large number of invalidated pages, thepage is relocated to another LSE so that the present LSE may bereclaimed. The locations of pages or groups of pages in the datahandling information 320 and the mappings therein are updatedaccordingly when pages are relocated. A relocation metric, such as acount of the number of relocations, is tracked by page in relocationmetrics 340.

In one embodiment, the control 200 of FIG. 1 also tracks heat metrics310 of the data in the memory, such as secondary cache 300.

One example of a heat metric is a count of the number of times that thepage of data has been accessed (“hit”) since it was last stored withinthe data storage system. For example, data may be located in datastorage 204 and be read by a host system and stored additionally in thesecondary cache memory 300. Further, newly written data may be stored incache memory 300, pending movement into data storage 204. The number ofhits can be implemented in the form of a counter in the metadata entryfor each page 320, for example.

Other examples of heat metrics comprise a number of hits of a page overa limited period of time or a predetermined number of requestsprocessed. The heat metrics may alternatively comprise a ratio of hitsto a page compared to an average of hits to all pages.

Still further, the heat metrics may be aged, giving less weight to hitsthat are not recent. The aging may be linear or exponential.

As discussed above, while some pages, such as pages 295 of LSE 280, areinvalidated, the valid pages 297 may be relocated, and may be relocatedmany times, as the LSEs are combined and rearranged to reclaim space inthe form of empty LSEs. In one embodiment, the control 200 of FIG. 1also tracks the location of the data with the data handling information320 and updates the location information when the data is relocatedwithin the data storage memory, such as secondary cache memory 300. Thecontrol 200 tracks the relocation metrics 340 for each page.

In one embodiment, the relocation metrics 340 comprise a count of thenumber of times that a page has been relocated during reclamationprocess iterations. To avoid the possibility of the ratio having ananswer of infinity, the denominator relocation metric r(p) may be givenan initial value of “1”.

The relocation metrics 340 and the heat metrics 310 may both bedetermined by counters for each page associated with the metadata 320.

In one embodiment, the amount of data that is invalidated is increasedby selectively relocating only pages that meet a heat utility threshold.The rest of the pages will be invalidated and removed from the cache.That is, many cold pages will be treated as invalid pages during thereclamation process. Thus, a large number of relocation writes will beavoided, effectively resulting in higher memory performance.

Still referring to FIGS. 2, 3 and 4, the control 200 of FIG. 1determines the heat metrics h(p) for pages of data stored in the datastorage memory 300; and determines the relocation metrics r(p) relatedto relocation of the data within the data storage memory. Then, theutility metrics u(p) of the data are determined relating the heatmetrics to the relocation metrics for the data. Data whose utilitymetric fails a utility metric threshold T, is invalidated, making itsspace available for space reclamation. In one embodiment, the utilitymetric comprises a ratio of the heat metric to the relocation metric, informula terms: u(p)=h(p)/r(p).

Thus, data that otherwise may be saved, but that fails the utilitymetric threshold T, is instead invalidated, and does not have to berelocated in the data storage memory 300.

In step 400, a page 285 “p” is nominated for eviction, perhaps by an LRUalgorithm 330.

In step 410, the page is tested, for example, by fetching the heatmetric 310 and the relocation metric 340 for the page. The utilitymetric for the page, for example the ratio of the heat metric to therelocation metric, u(p)=h(p)/r(p), is determined in step 420.

In the instance where a page has been recently added to the data storagememory 300 and happens to be relocated, the heat metric may be coldsince there has been little opportunity for hits and the relocationgives an artificially low utility metric. Thus, in step 430, the timingof the addition to storage is checked, and, if the page has recentlybeen added to the storage, it is exempted from space reclamationeligibility, and, in step 440, is made available for relocation, savingit in the memory 300. Thus, the system allows the page to remain in thememory for some time to give it a chance for getting hits.

Step 430 may be arranged to apply other space management policy 350 toexempt a page from space reclamation eligibility. Some examples comprisemaking data that has been hit only once is eligible for reclamation, butdata that has been hit more than twice is ineligible for a period oftime after the last hit; or data that arrived in the memory bysequential reads is eligible for reclamation, but data that arrived dueto random reads is ineligible for reclamation.

If step 430 determines that a page is eligible for eviction, it becomesa tentative space reclamation victim page.

Step 460 provides the utility threshold T. Threshold T may be a fixedvalue, or may be set dynamically.

In one embodiment, the utility metric threshold T is determined from anaverage of utility metrics for data of the data storage memory 300.

In another embodiment, the average of utility metrics for data of thedata storage memory is determined over a period of time.

In still another embodiment, the utility metric threshold T isdynamically determined from an average of utility metrics for data ofthe data storage identified in an LRU list 330 for the data storagememory 300.

Step 470 compares the utility metric for the page p that is thetentative space reclamation victim u(p) to the threshold T. The intentis to save and relocate only those pages that have high utility, and toinvalidate pages that fail the utility metric threshold T, so that theydo not have to be relocated in the data storage memory.

Thus, if step 470 determines that the utility metric for page p fails autility metric threshold T, step 480 makes the page available for spacereclamation. If step 470 determines that the utility metric for page pmeets or exceeds the utility metric threshold T, step 440 makes the pageavailable for relocation, exempting the page from space reclamation andsaving it in the memory 300.

Step 490 either moves to the next page, or advances to conduct therelocations and rearrangement of the LSEs. The relocation of the pagescomprises determining the invalidated pages of the data eligible forreclamation; and selecting at least one log structured extent having thegreatest number of invalidated pages, for relocating valid pages thereininto another log structured extent, to reclaim the selected logstructured extent.

Should the memory 300 be managed in a log-structured manner withoutusing LSEs, the space is reclaimed over the entire memory, and therelocation algorithm, relocation metrics, utility metrics, and thresholdare arranged to the specifics of the memory arrangement.

A person of ordinary skill in the art will appreciate that theembodiments of the present invention, disclosed herein, including thecomputer-implemented storage control 200 for reclaiming space of a datastorage memory 300 of the storage system 110 of FIG. 1, and thefunctionality provided therein, may be embodied as a system, method orcomputer program product. Accordingly, embodiments of the presentinvention may take the form of an entirely hardware embodiment, anentirely software embodiment (including firmware, resident software,micro-code, etc.) or a combination thereof, such as an embodimentcombining software and hardware aspects that may all generally bereferred to herein as a “circuit,” “module” or “system.” Furthermore,embodiments of the present invention may take the form of a computerprogram product embodied in one or more non-transient computer readablemedium(s) having computer readable program code embodied thereon.

Any combination of one or more non-transient computer readable medium(s)may be utilized. The computer readable medium may be a computer readablestorage medium. A computer readable storage medium may be, for example,but not limited to, an electronic, magnetic, optical, electromagnetic,infrared, or semiconductor system, apparatus, or device, or any suitablecombination of the foregoing. More specific examples (a non-exhaustivelist) of the computer readable storage medium would include thefollowing: an electrical connection having one or more wires, a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM),an erasable programmable read-only memory (EPROMor Flash memory), an optical fiber, a portable compact disc read-onlymemory (CD-ROM), an optical storage device, a magnetic storage device,or any suitable combination of the foregoing. In the context of thisdocument, a computer readable storage medium may be any tangible mediumthat can contain or store a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for embodiments of thepresent invention may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Smalltalk, C++ or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider).

Embodiments of the present invention are described above with referenceto flowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer program instructions. These computer program instructions maybe provided to a processor of a general purpose computer, specialpurpose computer, or other programmable data processing apparatus toproduce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

Those of skill in the art will understand that changes may be made withrespect to the methods discussed above, including changes to theordering of the steps. Further, those of skill in the art willunderstand that differing specific component arrangements may beemployed than those illustrated herein.

While the preferred embodiments of the present invention have beenillustrated in detail, it should be apparent that modifications andadaptations to those embodiments may occur to one skilled in the artwithout departing from the scope of the present invention as set forthin the following claims.

What is claimed is:
 1. A method for reclaiming space of a data storagememory of a data storage memory system, comprising: determining heatmetrics of data stored in said data storage memory; determiningrelocation metrics related to relocation of said data within said datastorage memory, said relocation metrics comprising a count of the numberof times said data has been relocated during reclamation processiterations; determining utility metrics of said data relating said heatmetrics to said relocation metrics for said data; and making said datawhose utility metric fails a utility metric threshold, available forspace reclamation.
 2. The method of claim 1, additionally comprising:exempting from space reclamation said data whose utility metric meets orexceeds said utility metric threshold; and exempting from spacereclamation eligibility, data recently added to said data storagememory.
 3. The method of claim 1, additionally comprising: exemptingfrom space reclamation eligibility, data designated as ineligible byspace management policy.
 4. The method of claim 1, wherein said utilitymetric threshold is determined from an average of utility metrics fordata of said data storage memory.
 5. The method of claim 4, wherein saidaverage of utility metrics for data of said data storage memory isdetermined over a period of time.
 6. The method of claim 4, wherein saidaverage of utility metrics for data of said data storage memory isdetermined over a predetermined number of space reclamation requestsprocessed.
 7. The method of claim 1, wherein said utility metricthreshold is dynamically determined from an average of utility metricsfor data of said data storage identified in an LRU list for said datastorage memory.
 8. The method of claim 1, wherein said data stored insaid data storage memory is in the form of pages, and wherein saidutility metric threshold for a tentative space reclamation victim pageof said data, is dynamically determined from an average of utilitymetrics for pages of said data having similar heat metrics to saidtentative space reclamation victim.
 9. The method of claim 1, whereinsaid data stored in said data storage memory is in the form of pages inlog structured extents; and said method additionally comprises:invalidating pages of said data eligible for reclamation; selecting atleast one log structured extent having the greatest number ofinvalidated pages, for relocating valid pages therein into another logstructured extent, to reclaim said selected log structured extent. 10.The method of claim 9, wherein said heat metric is based upon the numberof hits to data whose heat metric is being determined; and saidrelocation metric is based upon the number of times said data whoserelocation metric is being determined is relocated to another logstructured extent.
 11. A computer-implemented data storage memory systemcomprising: at least one data storage memory; and a control forreclaiming space of said data storage memory, said control: determiningheat metrics of data stored in said data storage memory; determiningrelocation metrics related to relocation of said data within said datastorage memory, said relocation metrics comprising a count of the numberof times said data has been relocated during reclamation processiterations; determining utility metrics of said data relating said heatmetrics to said relocation metrics for said data; and making said datawhose utility metric fails a utility metric threshold, available forspace reclamation.
 12. The computer-implemented data storage memorysystem of claim 11, wherein said control additionally: exempting fromspace reclamation said data whose utility metric meets or exceeds saidutility metric threshold; and exempting from space reclamationeligibility, data recently added to said data storage memory.
 13. Thecomputer-implemented data storage memory system of claim 11, whereinsaid control additionally: exempting from space reclamation eligibility,data designated as ineligible by space management policy.
 14. Thecomputer-implemented data storage memory system of claim 11, whereinsaid utility metric threshold is determined from an average of utilitymetrics for data of said data storage memory.
 15. Thecomputer-implemented data storage memory system of claim 14, whereinsaid average of utility metrics for data of said data storage memory isdetermined over a period of time.
 16. The computer-implemented datastorage memory system of claim 14, wherein said average of utilitymetrics for data of said data storage memory is determined over apredetermined number of space reclamation requests processed.
 17. Thecomputer-implemented data storage memory system of claim 11, whereinsaid utility metric threshold is dynamically determined from an averageof utility metrics for data of said data storage identified in an LRUlist for said data storage memory.
 18. The computer-implemented datastorage memory system of claim 11, wherein said data stored in said datastorage memory is in the form of pages, and wherein said utility metricthreshold for a tentative space reclamation victim page of said data, isdynamically determined from an average of utility metrics for pages ofsaid data having similar heat metrics to said tentative spacereclamation victim.
 19. The computer-implemented data storage memorysystem of claim 11, wherein said data stored in said data storage memoryis in the form of pages in log structured extents; and said methodadditionally comprises: invalidating pages of said data eligible forreclamation; selecting at least one log structured extent having thegreatest number of invalidated pages, for relocating valid pages thereininto another log structured extent, to reclaim said selected logstructured extent.
 20. The computer-implemented data storage memorysystem of claim 19, wherein said heat metric is based upon the number ofhits to data whose heat metric is being determined; and said relocationmetric is based upon the number of times said data whose relocationmetric is being determined is relocated to another log structuredextent.
 21. A computer program product for reclaiming space of a datastorage memory of a data storage memory system, said computer programproduct comprising computer-usable storage medium having non-transientcomputer-usable program code embodied therein, said computer-usableprogram code comprising: computer-usable program code to determine heatmetrics of data stored in said data storage memory; computer-usableprogram code to determine relocation metrics related to relocation ofsaid data within said data storage memory, said relocation metricscomprising a count of the number of times said data has been relocatedduring reclamation process iterations; computer-usable program code todetermine utility metrics of said data relating said heat metrics tosaid relocation metrics for said data; and computer-usable program codeto make said data whose utility metric fails a utility metric threshold,available for space reclamation.
 22. The computer program product ofclaim 21, additionally comprising: computer-usable program code to makesaid data whose utility metric meets or exceeds said utility metricthreshold exempted from space reclamation; and computer-usable programcode to exempt from space reclamation eligibility, data recently addedto said data storage memory.
 23. The computer program product of claim21, additionally comprising: computer-usable program code to exempt fromspace reclamation eligibility, data designated as ineligible by spacemanagement policy.
 24. The computer program product of claim 21, whereinsaid utility metric threshold is determined from an average of utilitymetrics for data of said data storage memory.
 25. The computer programproduct of claim 21, wherein said utility metric threshold isdynamically determined from an average of utility metrics for data ofsaid data storage identified in an LRU list for said data storagememory.
 26. The computer program product of claim 21, wherein said datastored in said data storage memory is in the form of pages, and whereinsaid utility metric threshold for a tentative space reclamation victimpage of said data, is dynamically determined from an average of utilitymetrics for pages of said data having similar heat metrics to saidtentative space reclamation victim.
 27. The computer program product ofclaim 21, wherein said data stored in said data storage memory is in theform of pages in log structured extents; and additionally comprising:computer-usable program code to invalidate pages of said data eligiblefor reclamation; and computer-usable program code to select at least onelog structured extent having the greatest number of invalidated pages,for relocating valid pages therein into another log structured extent,to reclaim said selected log structured extent.
 28. The computer programproduct of claim 27, wherein said heat metric is based upon the numberof hits to data whose heat metric is being determined; and saidrelocation metric is based upon the number of times said data whoserelocation metric is being determined is relocated to another logstructured extent.